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Carbon emissions in agricultural production activities have become an important source of accelerating climate warming. At present, low-carbon agriculture is not only an important means to mitigate climate warming, but also a necessary process of transformation from traditional agriculture to modern agriculture. Therefore, to achieve the sustainable development of agriculture in China’s Western Taiwan Straits Economic Zone (WTS Economic Zone), the governments should vigorously promote the upgrading and realize the development of low-carbon agriculture. By adopting the latest emission coefficients and the ordered weighted averaging (OWA) aggregation operator, this paper selected agricultural land use, rice paddies, crop production, livestock manure storage and livestock enteric fermentation as the five carbon emission sources, and measured agricultural carbon emissions in the WTS Economic Zone from 2010 to 2017. Thus, from the time perspective, the average agricultural carbon emissions in the WTS Economic Zone showed a fluctuating downward trend, from 762.64 × 10³ tonnes in 2010 to 710.02 × 10³ tonnes in 2017. From the spatial perspective, total agricultural carbon emissions among regions are quite different. To further clarify the factors affecting agricultural carbon emissions in the WTS Economic Zone, by applying the geographically and temporally weighted regression (GTWR) model, this paper selected the research and development intensity, the added value of agriculture, the proportion of agricultural labour force, the overall level of urbanization, per capita disposable income of rural residents and per capita arable land areas as the influencing factors, and then measured the direction and degree of the influences on agricultural carbon emissions in different temporal-spatial backgrounds. The results showed that the added value of agriculture, the proportion of agricultural labour force and per capita arable land areas had positive influences on agricultural carbon emissions, while the research and development intensity, the overall level of urbanization and per capita disposable income of rural residents had negative impacts. Although agricultural carbon emissions in the WTS Economic Zone have decreased in recent years, further measures can be taken to effectively reduce agricultural carbon emissions, and ultimately promote the development of lowcarbon agriculture according to the results of this study. [ABSTRACT FROM AUTHOR]

Business English teaching quality evaluation Business English is a new type of composite specialty, which is a discipline innovation made by China's higher education to adapt to the new market demand and international standards since the reform and opening up. Over the past 20 years, it has cultivated a number of compound talents for the cause of China's reform and opening up. However, the backwardness of business English theoretical research has greatly restricted the development of business English. At present, Business English has been officially approved as a new major for undergraduate enrollment by the Ministry of Education of the People's Republic of China. Its subject nature, specialty structure, training objectives, and specialty compound characteristics need to be qualitatively studied theoretically. The business English teaching quality evaluation is viewed as the multiple attribute decision making (MADM) issue. In this paper, we connect the geometric Heronian mean (GHM) operator and power geometric (PG) with 2-tuple linguistic neutrosophic numbers (2TLNNs) to propose the generalized 2-tuple linguistic neutrosophic power geometric HM (G2TLNPGHM) operator. Then, the G2TLNGHM operator is applied to deal with the MADM problems under 2TLNNs. Finally, an example for business English teaching quality evaluation is used to show the proposed methods. Some comparative analysis and parameter influence analysis are fully given. The results show that the built algorithms method is useful for business English teaching quality evaluation. [ABSTRACT FROM AUTHOR]

Operations on inputs are partially or completely decisive for information aggregation, and parameterized operations are widely used due to their flexibility in practice. The Bonferroni mean is a typical mean operator taking into account interrelationships between any two input variables. In this paper, the Hamacher operations are considered in constructing q-rung orthopair fuzzy aggregation operators combined with the Bonferroni mean. First, explicit expressions of aggregated results by the q-rung orthopair fuzzy Hamacher Bonferroni mean operator are presented without intermediate variables, which would certainly improve the computational efficiency. Then, limits of these resulting aggregations are examined with respect to parameters within Hamacher operations and Bonferroni mean, respectively. The obtained conclusions reveal relations among the current mean operator and some existing ones, and some numerical examples are given to facilitate the conceptual arguments. Finally, the developed operator is employed to evaluate the service quality of passenger airlines in Taiwan, China, and a comparative analysis is presented in this study. [ABSTRACT FROM AUTHOR]

Individual opinion is one of the vital factors influencing the consensus in group decision-making, and is often uncertain. The previous studies mostly used probability distribution, interval distribution or uncertainty distribution function to describe the uncertainty of individual opinions. However, this requires an accurate understanding of the individual opinions distribution, which is often difficult to satisfy in real life. In order to overcome this shortcoming, this paper uses a robust optimization method to construct three uncertain sets to better characterize the uncertainty of individual initial opinions. In addition, we used three different aggregation operators to obtain collective opinions instead of using fixed values. Furthermore, we applied the numerical simulations on flood disaster assessment in south China so as to evaluate the robustness of the solutions obtained by the robust consensus models that we proposed. The results showed that the proposed models are more robust than the previous models. Finally, the sensitivity analysis of uncertain parameters was discussed and compared, and the characteristics of the proposed models were revealed. [ABSTRACT FROM AUTHOR]

In view of the decision‐making problem that the alternatives actively participate in the decision‐making process and present competitive behavior, this paper proposes a new type of aggregation operator called the competitive behavior induced ordered weighted averaging (CB‐IOWA) operator. The primary characteristic of the CB‐IOWA operator is that the alternative is permitted to highlight its competitive advantage through the order‐inducing variables and the weighting vector. A method is introduced to determine the final weighting vector based on the weights provided by different alternatives that can reflect their competitive advantages. The final weights are calculated by maximizing the closeness degree between the final weights and the ones provided the alternatives. The main properties of the CB‐IOWA operator are discussed, such as commutativity, boundness, and monotonicity under certain condition. Finally, an application example regarding the competitive development of the economy‐environment of four cities in China is provided to illustrate the usage of the CB‐IOWA operator. The validity of the operator is checked by comparison with the weighted arithmetic averaging operator representing noncompetitive behavior. [ABSTRACT FROM AUTHOR]

Large-scale group decision-making (LSGDM) deals with complex decision- making problems which involve a large number of decision makers (DMs). Such a complex scenario leads to uncertain contexts in which DMs elicit their knowledge using linguistic information that can be modelled using different representations. However, current processes for solving LSGDM problems commonly neglect a key concept in many real-world decision-making problems, such as DMs' regret aversion psychological behavior. Therefore, this paper introduces a novel consensus based linguistic distribution LSGDM (CLDLSGDM) approach based on a statistical inference principle that considers DMs' regret aversion psychological characteristics using regret theory and which aims at obtaining agreed solutions. Specifically, the CLDLSGDM approach applies the statistical inference principle to the consensual information obtained in the consensus process, in order to derive the weights of DMs and attributes using the consensus matrix and adjusted decision-making matrices to solve the decision-making problem. Afterwards, by using regret theory, the comprehensive perceived utility values of alternatives are derived and their ranking determined. Finally, a performance evaluation of public hospitals in China is given as an example in order to illustrate the implementation of the designed method. The stability and advantages of the designed method are analyzed by a sensitivity and a comparative analysis. [ABSTRACT FROM AUTHOR]

With the rapid growth of the market economy, ranked according to the proportion of consumption, China has become the world's second, a lot of foreign companies increasingly value the Chinese market, and constantly improve their design philosophy and business philosophy. Throughout today's advertising industry, it can be seen in the many excellent advertising designs, non-mainstream appearance has a high rate of non-mainstream cultural elements is a common design approach in the design of modern advertising, and more and more people sought after. In this paper, we investigate the multiple attribute decision making problems with fuzzy number intuitionistic fuzzy information. Firstly, we analyze several operations on the fuzzy number intuitionistic fuzzy sets. Then, we use the induced fuzzy number intuitionistic fuzzy Hamacher correlated average (IFNIFHCA) operator to solve multiple attribute decision making with the fuzzy number intuitionistic fuzzy information. Finally, an illustrative example for evaluating the advertisement design effects is given to verify the developed approach. [ABSTRACT FROM AUTHOR]

Using multi-criteria decision making (MCDM) technique to rank alternatives is a well-known area of study in which aggregation operators, such as ordered weighted averaging (OWA) and induced OWA (IOWA) operators, play an important role in merging information and producing an overall ranking. The distance measures from ideal argument values in aggregation operators have gained attention in recent literature. Distance measures are traditionally used as argument variables, which leads to the depiction that the attribute cannot be aggregated directly. In this paper, a generalized form of distance-induced OWA (DIOWA) operators is proposed with distance measures used as order-inducing variables. A distinctive benefit of DIOWA operators is that they permit us to consider ideal argument values while simultaneously also taking the attribute values as argument variables. Three variants of DIOWA operators are proposed and investigated, namely a) the Hamming distance-induced OWA (HDIOWA) operator, b) the normalized Hamming distance-induced OWA (NHDIOWA) operator, and c) the weighted Hamming distance-induced OWA (WHDIOWA) operator. We highlight their important properties and provide proofs to necessary theorems, and also suggest the determination methods for calculating their associated weights. We discuss further extensions of the proposed DIOWA operators with the help of generalized and quasi-arithmetic means. We discuss the use of our proposed family of operators for two different decision making situations, and demonstrate their validity by an illustrative numerical example. Finally, we apply the proposed operators to a real-life problem of ranking Chinese provinces for their science and technology (S&T) development levels. The proposed operators are shown to be a useful addition to the aggregation toolbox for decision analysts. [ABSTRACT FROM AUTHOR]

In order to further investigate the level of online medical services in China and improve the medical experience of patients, this study aims to establish an online review-driven picture fuzzy multi-criteria group decision-making (MCGDM) approach for the online medical service evaluation of doctors. First, based on the Aczel–Alsina t-norm and t-conorm, the normal picture fuzzy Aczel–Alsina operations involving a variable parameter are defined to make the corresponding operations more flexible than other operations. Second, two picture fuzzy Aczel–Alsina aggregation operators are developed, and the corresponding properties are discussed as well. Third, combined with the online review information of China's medical platform Haodaifu, the online review-driven evaluation attributes and their corresponding weights are obtained, which can make the evaluation model more objective. Fourth, an extended normal picture fuzzy complex proportional assessment (COPRAS) decision-making method for the service quality evaluation of online medical services is proposed. Finally, an empirical example is presented to verify the feasibility and validity of the proposed method. A sensitivity analysis and a comparison analysis are also conducted to demonstrate the effectiveness and flexibility of the proposed approach. [ABSTRACT FROM AUTHOR]

A learning management system (LMS) is a web-based application or software platform computed to facilitate the development, tracking, management, reporting, and delivery of education and training programs. Many valuable and dominant factors are working behind the Learning Management System (LMS), but no one can find which factor is most important and valuable for LMS during COVID-19 among the following five alternatives, called Improved Accessibility, Blended Learning, Collaboration and Communications, Assessment and Evaluation, and Administrative Efficiency. For this, first, we derive the techniques of bipolar complex hesitant fuzzy (BCHF) sets, and then we evaluate some flexible operational laws, called Algebraic operational laws and Aczel-Alsina operational laws. Secondly, using the above techniques, we elaborate the technique of BCHF Aczel-Alsina power averaging (BCHFAAPA), BCHF Aczel-Alsina power weighted averaging (BCHFAAPWA), BCHF Aczel-Alsina power geometric (BCHFAAPG), and BCHF Aczel-Alsina power weighted geometric (BCHFAAPWG) operators. Some basic properties are also investigated for each proposed operator. Further, to evaluate the problem concerning LMS, we compute the multi-attribute decision-making (MADM) techniques for invented operators. Finally, we select some prevailing operators and try to compare their ranking results with our proposed results to enhance the worth and capability of the invented theory. [ABSTRACT FROM AUTHOR]

Massive open online courses (MOOCs) are very popular in China, and it is very important to evaluate and improve them. In this paper, a new evaluation method for MOOCs based on multi‐attribute group decision‐making is proposed. First, an evaluation index system of MOOCs is constructed, which contains six elements and 16 indicators, and multigranular unbalanced hesitant fuzzy linguistic term set (MGUHFLTS) is adopted to describe these indicators. Then based on MGUHFLTS, the aggregation operators are developed, including the multigranularity unbalanced hesitant fuzzy linguistic weighted averaging operator and the multigranularity unbalanced hesitant fuzzy linguistic order weighted averaging operator, moreover, a novel multi‐attributive border approximation area comparison model based on MGUHFLTS is proposed. This model is testified validity and superiority by comparison with other three methods and is applied in evaluation of MOOCs. After ranking five MOOCs, each indicator is analyzed to show how they influenced each element and suggestions are given. [ABSTRACT FROM AUTHOR]

We establish a decision making model for evaluating hydrogen production technologies in China, based on interval-valued intuitionistic fuzzy set theory. First of all, we propose a series of interaction interval-valued intuitionistic fuzzy aggregation operators comparing them with some widely used and cited aggregation operators. In particular, we focus on the key issue of the relationships between the proposed operators and existing operators for clear understanding of the motivation for proposing these interaction operators. This research then studies a group decision making method for determining the best hydrogen production technologies using interval-valued intuitionistic fuzzy approach. The research results of this paper are more scientific for two reasons. First, the interval-valued intuitionistic fuzzy approach applied in this paper is more suitable than other approaches regarding the expression of the decision maker's preference information. Second, the results are obtained by the interaction between the membership degree interval and the nonmembership degree interval. Additionally, we apply this approach to evaluate the hydrogen production technologies in China and compare it with other methods. [ABSTRACT FROM AUTHOR]

Computer network security evaluation is a basic work to determine the security performance of the network system and implement the network security management. It involves organizational management, network technology, personnel psychology, social environment and other factors. In recent years, with the rapid development of information technology in China, the problem of computer network security has become increasingly prominent. Although domestic and foreign scholars have sought effective methods of network security evaluation from different aspects and using different methods, many factors involved in network security are difficult to quantify, so far, there is no relatively mature quantitative evaluation method of network security. The computer network security evaluation is classical multiple attribute decision making (MADM) problems. In this article, based on projection measure, we shall introduce the projection models with q-rung orthopair fuzzy information. First of all, the definition of q-rung orthopair fuzzy sets (q-ROFSs) is introduced. In addition, to fuse overall q-rung orthopair fuzzy evaluation information, two aggregation operators including q-ROFWA and q-ROFWG operators is introduced. Furthermore, combine projection with q-ROFSs, we develop the projection models with q-rung orthopair fuzzy information. Based on developed weighted projection models, the multiple attribute decision making model is established and all computing steps are simply depicted. Finally, a numerical example for computer network security evaluation is given to illustrate this new model and some comparisons between the new proposed models and q-ROFWA and q-ROFWG operators are also conducted to illustrate advantages of the new built method. [ABSTRACT FROM AUTHOR]

The financial risk evaluation of new energy vehicle (NEV) industry is conducive to the popularization of NEVs, to encourage more investment into the NEV industry, and to promote the improvement of the risk control system. When evaluating the performance of NEV industry in China, it is usually full of uncertainty and dynamic. q-Rung orthopair fuzzy set (q-ROFS) has the characteristics of non-membership and membership with adjustable parameterization q , which is a very effective mathematical model to capture uncertainty. In this paper, the q-rung orthopair fuzzy (q-ROF) distance measure based triangle orthocenter is given. Then, q-ROF score function (SF) based distance measure is proposed for disposing of comparison issue. Moreover, we present nonlinear comprehensive weighting method by integrating subjective weight information and objective weight information (determining by water-filling theory). In order to solve the counter-intuitive phenomena and dynamic trend issue, the dynamic q-ROF aggregation operators are investigated and their properties are proved. Whereafter, q-ROF multi-criteria decision making (MCDM) approach based projection ranking by similarity to referencing vector (PRSRV) is proposed for evaluating financial risk of NEV industry, along with the sensitivity analysis. Finally, a comparison with some existing MCDM methods states that the presented method has strong data adaptability. • Distance measure and similarity measure based triangle orthocenter are developed. • New q-ROF score function based distance measure is introduced. • Novel dynamic q-ROF aggregation operators is proposed. • New combined determining weight model is constructed. • The developed PRSRV method holds application prospect in financial risk assessment of NEV industry. [ABSTRACT FROM AUTHOR]

River course is the path of carrying river flow and the blood of modern economic and social development. River operation management has attracted great attention from governments and water conservancy circles all over the world. In China, the river operation management mode refers to the combination of two dimensions: The organization method of river operation management and the bearing and use method of river maintenance fund. Based on the practice of China, we used a two-dimensional matrix method to construct a feasible mode set, including 12 modes, according to the various organization methods of river operation management and the bearing and use methods of river maintenance fund over the years in China. We also compared and analyzed the advantages, disadvantages, and applicable conditions of these 12 river operation management modes. In particular, we investigated the main rivers of 19 provinces and municipalities in China, identified the main factors of the river operation management mode, further identified 5 key indexes, and constructed a decision-making index system for the river operation management mode. We used the intuitionistic fuzzy hybrid average (IFHA) and intuitionistic fuzzy weighted average (IFWA) operators to construct a set of river operation management mode selection method based on intuitionistic fuzzy decision-making. A case study was conducted to select the operation management mode for the Heilongjiang section of Songhua River, using the method put forward in this paper. This study can promote water resource management research and prepare for a possible future sustainability emergency. [ABSTRACT FROM AUTHOR]

Aggregation operators consist of mathematical functions that enable the combining and processing of different types of information. The aim of this work is to present the main contributions in this field by a bibliometric review approach. The paper employs an extensive range of bibliometric indicators using the Web of Science (WoS) Core Collection and Scopus datasets. The work considers leading journals, articles, authors, institutions countries and patterns. This paper highlights that Xu is the most productive author and Yager is the most influential author in the field. Likewise, China is leading the field with many new researchers who have entered the field in recent years. This discipline has been strengthening to create a unique theory and will continue to expand with many new theoretical developments and applications. • Overview of the aggregation operators. • Bibliometric analysis. • VOS viewer visualization. • Web of Science. [ABSTRACT FROM AUTHOR]

Accurate prediction of long‐term and short‐term clean energy production is the basis for understanding short‐term clean energy supply capacity, long‐term clean energy development trend and evaluating the effect of energy policies. However, under the circumstances of the large time span, the insufficient data samples and the periodic characteristics of seasonal clean energy production make the traditional grey prediction model prone to produce forecasting deviations. Given this situation, a novel seasonal fractional‐order full‐order time power discrete grey prediction model is initially proposed to deal with long‐term clean energy production sequences featured with nonlinearity and periodicity. Based on the proposed model, we also propose a data‐based algorithm to select the model structure adaptively. To prove the practicability of the new model for nonlinear long‐term development trend, monthly periodic time series and quarterly periodic time series, this article uses the new model to predict annual hydropower capacity in North America, monthly natural gas production in China and quarterly solar power generation in China. And the prediction results are compared with the existing grey models and non‐grey prediction models. Different methods including GM (1,1), DGM (1,1), NGM (1,1), ARGM (1,1), ENGM (1,1), Verhulst, CCRGM (1,1), FOTP‐DGMr (1,1), PFSM (1,1), Holt‐winters model, SARIMA model, SGM, HP‐GM and DGGM are used as benchmarks. In experiments, the MAPE of the proposed model is 2.92%, 2.43%, and 7.87%, respectively. The results of empirical analysis indicate that the proposed model generally outperform the benchmark model as it can well capture nonlinear long‐term development trend and seasonal characteristics. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes a new approach based on possibility degree to solve multi-criteria decision making (MCDM) problems in which the criteria value takes the form of interval type-2 fuzzy number. First, a new expected value function is defined and an optimal model based on maximizing deviation method is constructed to obtain weight coefficients when criteria weight information is partially known. Then, the overall value of each alternative is calculated by the defined aggregation operators. Furthermore, a new possibility degree, which is proposed to overcome some drawbacks of the existing methods, is introduced for comparisons between the overall values of alternatives to construct a possibility degree matrix. Based on the constructed matrix, all of the alternatives are ranked according to the ranking vector derived from the matrix, and the best one is selected. Finally, the proposed method is applied to a case study on the overseas minerals investment for one of the largest multi-species nonferrous metals companies in China and the results demonstrate the feasibility of the method. [Copyright &y& Elsevier]

Group emergency decision-making is an uncertain and dynamic process, in which the decision makers may be bounded rational and have a risk appetite. To depict the vague qualitative assessments, the probabilistic linguistic term sets are employed to express the perceptions of decision makers. First, considering the regret-aversion of the decision makers' psychological characteristic, the value function and the regret-rejoice function in the regret theory are modified to adapt the probabilistic linguistic information. Second, the definition and aggregation operators of the probabilistic linguistic time variable are proposed to describe and aggregate the dynamic decision information. Third, the probabilistic linguistic models based on the dynamic reference point method and the regret theory are studied to maximise the expectation-levels of alternatives at the relative time point. The proposed method is applied to select the optimal response strategy for the outbreak of COVID-19 in China. Finally, the comparative analysis is designed to verify the applicability and reasonability of the proposed method. [ABSTRACT FROM AUTHOR]